1. Field of the Invention
The invention relates to a cross technology field combining the aerospace technology with image processing, and more particularly to a method for restoring and enhancing a space based image of point or spot objects in large field of view.
2. Description of the Related Art
During space-based observation to the earth by the imaging detection devices, due to limitation of design and manufacturing technology of the imaging detection devices, image quality is to be reduced, and image distortion or blur is to occur. Particularly, signals of point or spot objects are to be weakened as far as spot or point objects are concerned, and thus resulting in missing of the point sources or the porphyritic objects. Blur caused by the imaging sensor itself can be approximately represented by a point spread function model. However, traditional imaging sensors in a small field of view using a space-invariant point spread function degraded model cannot accurately reflects imaging distortion generated by imaging sensors with a large field of view. More importantly, with time passing by, distortion of the imaging system is to increase after the system is built up, and therefore how to develop a digital processing method capable of self-adaptively correcting distortion and blur and improving performance of imaging sensors becomes an important research project, and is also a weak, pending and difficult problem at present.
Imaging distortion caused by the imaging sensors with a large field of view is represented by a space-variable point spread function, and characterized by variant time and space.
Assuming a point spread function of the distortion of the imaging sensor within certain exposure time is represented by PSF(x, y), which can be obtained by convoluting two point spread functions:
1. as for imaging blur caused by different distance between the photosensitive elements and the axis center of the imaging lens, an equivalent point spread function thereof is PSF1(r), where r represents the distance between the photosensitive elements and the axis center of the imaging lens or the center of the focal plane. As shown in FIGS. 2a-2e, since the manufacturing technique of the imaging sensor, imaging blur at a center of the focal plane caused by diffraction limit, namely PSF1(r), is relatively small. The larger the distance from the lens axis center is, the greater distortion of the imaging sensor is, which results in large imaging blur, and thus PSF1(r) is accordingly large (as shown in FIG. 2b).
2. as shown in FIG. 3a, a point spread function at a photosensitive element S(x, y) is PSF1(r)(r=√{square root over (x2+y2)}), a point object may complete fall on the photosensitive element, namely a point image with a pixel, or on two to four photosensitive elements (as shown in FIGS. 3b to 3d), here all these photosensitive elements generate response and change one point image into a point image with two to four pixels, which cause a blur effect. Likewise, spot objects larger than a photosensitive element falling on multiple photosensitive elements whereby causes additional blur, as shown in FIG. 3e. In other words, since imaging positions are different, point or spot objects with the same size form random, additional blur images on the discrete photosensitive element array of the focal plane of the imaging lens. The blur resulting from a discrete photosensitive element array of a digital imaging sensor can be represented by a random point spread function PSF2(x, y), and thus a total point spread function can be represented as:PSF(x,y)=PSF1(x,y)*PSF2(x,y)
To summarize, it is required to provide a new digital image processing technique capable of improving and correcting the above-mentioned imaging blur problems caused by imaging sensor system itself.